The use of personal computers and other digital hardware to process and display digital images has grown in popularity due to the ever increasing digital image and video content available on the Internet. One result of this growth in popularity is the increased complexity in retrieving desired images due to the large numbers of available images. Conventionally, the desired images are often retrieved through the file names of the images.
The file names, however, often do not provide an adequate description of the image or video content to enable a user to determine what the image or video content contains. As such, the contents of the images and videos stored on conventional databases are oftentimes stored with tags, which provide brief descriptions of the contents. For instance, an image containing a blue car on a black road may include tags such as, “car”, “blue”, and “road”. These tags are typically inputted into the database manually, which is both labor and time intensive.
Automated approaches to describing the images and videos have included, for instance, with respect to describing colors, systems based on color encodings which represent components of a color in terms of positions or coordinates in a multidimensional color space. In other words, colors have been mathematically represented using numerical data indicative of the position or coordinates in the color space. Although data regarding a color may specifically define a color with respect to the color space, these representations typically do not intuitively convey information regarding the color to humans.